Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Scaling Down, LiTting Up: Efficient Zero-Shot Listwise Reranking with Seq2seq Encoder-Decoder Models
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2312.16098.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T12:07:24.236039Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-14T19:52:52.360309Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 7d3cec29-c7cd-4e7a-a261-cf5452d5e8d8 · inbound
Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation cites this paper.
Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation Scaling Down, LiTting Up: Efficient Zero-Shot Listwise Reranking with Seq2seq Encoder-Decoder Models
Reference 93
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T12:07:24.236039Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e450d8a7-3c7d-45f2-bd7d-04e0f5de8977 · inbound
Counterfactual Query Rewriting to Use Historical Relevance Feedback cites this paper.
Counterfactual Query Rewriting to Use Historical Relevance Feedback Scaling Down, LiTting Up: Efficient Zero-Shot Listwise Reranking with Seq2seq Encoder-Decoder Models
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T00:26:20.235883Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a10e5d2c-2b05-4480-8f4b-85417550c32b · inbound
Rank-K: Test-Time Reasoning for Listwise Reranking cites this paper.
Rank-K: Test-Time Reasoning for Listwise Reranking Scaling Down, LiTting Up: Efficient Zero-Shot Listwise Reranking with Seq2seq Encoder-Decoder Models
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:40:11.506379Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fd4d8c7a-72cc-49e3-82b7-0bb4a286edb6 · inbound
Conventional Contrastive Learning Often Falls Short: Improving Dense Retrieval with Cross-Encoder Listwise Distillation and Synthetic Data cites this paper.
Conventional Contrastive Learning Often Falls Short: Improving Dense Retrieval with Cross-Encoder Listwise Distillation and Synthetic Data Scaling Down, LiTting Up: Efficient Zero-Shot Listwise Reranking with Seq2seq Encoder-Decoder Models
Reference 52
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:23:42.043574Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8699ba02-3e3f-485d-a0f2-f87f1c0502d1 · inbound
RankLLM: A Python Package for Reranking with LLMs cites this paper.
RankLLM: A Python Package for Reranking with LLMs Scaling Down, LiTting Up: Efficient Zero-Shot Listwise Reranking with Seq2seq Encoder-Decoder Models
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:20:40.711679Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ea948976-5eff-44b6-9769-cf22d4d729ba · inbound
JointRank: Rank Large Set with Single Pass cites this paper.
JointRank: Rank Large Set with Single Pass Scaling Down, LiTting Up: Efficient Zero-Shot Listwise Reranking with Seq2seq Encoder-Decoder Models
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:14:09.659069Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4ce76377-8243-45a1-aa11-147c6d5c2fd0 · inbound
How Good are LLM-based Rerankers? An Empirical Analysis of State-of-the-Art Reranking Models cites this paper.
How Good are LLM-based Rerankers? An Empirical Analysis of State-of-the-Art Reranking Models Scaling Down, LiTting Up: Efficient Zero-Shot Listwise Reranking with Seq2seq Encoder-Decoder Models
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T17:15:15.367334Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8b5d6e05-50b1-4e26-abd1-9b6e65c9bc6e · inbound
Rethinking the Necessity of Adaptive Retrieval-Augmented Generation through the Lens of Adaptive Listwise Ranking cites this paper.
Rethinking the Necessity of Adaptive Retrieval-Augmented Generation through the Lens of Adaptive Listwise Ranking Scaling Down, LiTting Up: Efficient Zero-Shot Listwise Reranking with Seq2seq Encoder-Decoder Models
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T08:27:51.794103Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 3dadcd33-4791-412c-af7f-46a6d84bebff · inbound
F-GRPO: Factorized Group-Relative Policy Optimization for Unified Candidate Generation and Ranking cites this paper.
F-GRPO: Factorized Group-Relative Policy Optimization for Unified Candidate Generation and Ranking Scaling Down, LiTting Up: Efficient Zero-Shot Listwise Reranking with Seq2seq Encoder-Decoder Models
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T19:52:52.363050Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.